Acute myeloid leukemia (AML) is characterized by uncontrolled proliferation of malignant myeloid precursor cells in the bone marrow. Genetic aberrations play an important role in pathogenesis as well as in classification of AML, which is relevant for accurate diagnosis, risk assessment and personalized treatment of AML. Genetic aberrations in AML are structurally diverse and currently measured by different diagnostic tests.
The aim of the study is to establish whole transcriptome messenger RNA sequencing (RNAseq) as single and flexible diagnostic platform for AML classification, prognostication, and choice of targeted agents.
Whole transcriptome RNA sequencing was performed on 100 AML cases and the bioinformatics pipeline HAMLET (Human AML Expedited Transcriptomics) was developed for simultaneous detection of fusion genes, small variants, long tandem duplications and gene expression. HAMLET results were validated by reference assays and targeted resequencing.
HAMLET accurately detected all fusion genes and overexpression of EVI1 irrespective of 3q26 aberrations. In addition, small variants in 13 genes that are often mutated in AML were called with 99.2% sensitivity and 100% specificity, and internal tandem duplications in FLT3 (FLT3-ITD) and partial tandem duplications in KMT2A (KMT2A-PTD) were detected by a novel algorithm based on soft clipped reads with 100% sensitivity and 97.1% specificity.
HAMLET accurately provides comprehensive diagnostic information relevant for AML classification, risk assessment and personalized therapy on a single technology platform. Instead of current AML diagnostics based on various assays that target selected aberrations, RNAseq-HAMLET represents a new diagnostic paradigm according to a “measure all – analyse relevant” approach, which can be adapted to advances in sequencing technology and novel insights in AML pathogenesis, and allows individual retrospective reassessment.